Ant Colony Optimization (ACO) Based Feature Selection and Extreme Learning Machine (ELM) for Chronic Kidney Disease Detection
S. Belina V.J. Sara, K. Kalaiselvi · SSRN Electronic Journal · 2018
ELM renders a unique learning atmosphere with the variety of feature mappings techniques that can be imposed in the classification area straight away. ELM has few constraints in the optimization. The formulated ELM classifier space is identified and can be subjected for the training of the network utilizing the ELM technique originally. The outputs of the experiment show that implementation of ELM classifier results in increased ability when correlated with the standard options i.e., extraction of input weights randomly. The experiment consists of the set of data that has 400 patients and has the problems of missing and noise information, where 250 patients have CKD and 150 patients have non CKD. At last cost-accuracy trade-off analysis is performed to determine an innovative CKD exploring the ELM technique with minimized computing interval and potential accuracy.